Validation of a multi-parameter algorithm for personalized contrast injection protocol in liver CT

Area of Science:

• Radiology
• Medical Imaging
• Personalized Medicine

Background:

• Optimizing contrast injection in liver computed tomography (CT) is crucial for image quality and patient safety.
• Personalized contrast delivery aims for reproducible liver enhancement around 50 Hounsfield Units (HU).

Purpose of the Study:

• To evaluate a novel algorithm for personalized contrast injection in liver CT.
• To achieve consistent liver enhancement centered at 50 HU.

Main Methods:

• Prospective, multicenter data collection of adult abdominal CT scans from September 2020 to August 2022.
• Utilized a web interface integrating radiology information system data and radiographer-inputted patient specifics (e.g., fat-free mass).
• Algorithm calculated contrast volume and injection rate, with kVp adjusted based on patient habitus (80, 100, or 120 kVp).

Main Results:

• 384 adult patients were enrolled.
• 72.1% of examinations achieved the target liver enhancement range of 40-60 HU.
• Iodine dose varied significantly with kVp and patient sex but not contrast agent type.

Conclusions:

• Validated a novel algorithm for personalized contrast injection in adult abdominal CT.
• The algorithm consistently achieves liver enhancement centered at 50 HU.
• Offers potential for improved diagnostic accuracy and patient management, especially for liver malignancies.